Heat-vulnerability mapping in the cities of Bern, Basel, and Zurich [final report].
Abstract
Urbanisation and the growing urban population have intensified the urban heat island (UHI)
effect, posing health risks. Although its impacts are not evenly distributed, understanding of
the spatial distribution of vulnerable populations to the UHI effect remains limited. To bridge
this knowledge gap, we aim to 1) evaluate demographics and socioeconomic factors
contributing to increased UHI exposure and 2) analyse the spatial distribution of vulnerability
by developing the Heat Vulnerability Index (HVI) in three Swiss cities (Basel, Bern, and
Zurich).
We collected individual-level population and household statistics (STATPOP) and companylevel
business statistics (STATENT) from the Swiss Federal Statistical Office. We used highresolution
simulated summer night-time temperature data in 2020 to calculate UHI intensity as
the temperature difference between the inner city and the rural surroundings. We assessed how
many critical infrastructures (healthcare facilities, schools and playgrounds) are in High UHI
areas, defined as districts exceeding the city-wide average UHI intensity. We evaluated the UHI
exposure on residents and workers by comparing the average number of populations between
Extreme UHI areas and Non-Extreme UHI areas, with Extreme UHI areas defined as districts
experiencing UHI intensity higher than the 90th percentile of the city-wide level. Subsequently,
we developed a Heat Vulnerability Index (HVI) by selecting key indicators having higher
mortality risks from the UHI effect proved by previous studies: older adults (aged ³ 65 years),
females, and individuals with the lowest socio-economic status. We then created a bivariate
map overlapping two layers of UHI and HVI and developed a web-based interactive tool to
visualise the health risks of the UHI effect.
Our results showed distinct UHI exposure and vulnerability patterns across different Swiss
cities. Although our bivariate maps showed partly similar patterns between cities, such as
concentrated vulnerability in densely populated urban cores, there were also city-specific
variations. For example, Bern exhibited high UHI and high HVI in its central area, while Zurich
experienced high UHI intensity in the city centre but had a relatively lower number of
vulnerable populations. Analysis of the workers’ exposure revealed that three cities consistently
showed a higher average number of workers in the service sector within Extreme UHI areas
than Non-Extreme UHI areas, likely due to the concentration of the service sector workers in
urban centres where UHI intensity is typically high. These differences highlight the need for
heat health risk assessments that consider the local context.
Our study examined the interaction between UHI exposure, demographics, and socio-economic
status in determining heat risks to health in Swiss cities. It offered a comprehensive assessment
framework for heat vulnerability explicitly tailored for key stakeholders such as urban planners
and public health officers.
effect, posing health risks. Although its impacts are not evenly distributed, understanding of
the spatial distribution of vulnerable populations to the UHI effect remains limited. To bridge
this knowledge gap, we aim to 1) evaluate demographics and socioeconomic factors
contributing to increased UHI exposure and 2) analyse the spatial distribution of vulnerability
by developing the Heat Vulnerability Index (HVI) in three Swiss cities (Basel, Bern, and
Zurich).
We collected individual-level population and household statistics (STATPOP) and companylevel
business statistics (STATENT) from the Swiss Federal Statistical Office. We used highresolution
simulated summer night-time temperature data in 2020 to calculate UHI intensity as
the temperature difference between the inner city and the rural surroundings. We assessed how
many critical infrastructures (healthcare facilities, schools and playgrounds) are in High UHI
areas, defined as districts exceeding the city-wide average UHI intensity. We evaluated the UHI
exposure on residents and workers by comparing the average number of populations between
Extreme UHI areas and Non-Extreme UHI areas, with Extreme UHI areas defined as districts
experiencing UHI intensity higher than the 90th percentile of the city-wide level. Subsequently,
we developed a Heat Vulnerability Index (HVI) by selecting key indicators having higher
mortality risks from the UHI effect proved by previous studies: older adults (aged ³ 65 years),
females, and individuals with the lowest socio-economic status. We then created a bivariate
map overlapping two layers of UHI and HVI and developed a web-based interactive tool to
visualise the health risks of the UHI effect.
Our results showed distinct UHI exposure and vulnerability patterns across different Swiss
cities. Although our bivariate maps showed partly similar patterns between cities, such as
concentrated vulnerability in densely populated urban cores, there were also city-specific
variations. For example, Bern exhibited high UHI and high HVI in its central area, while Zurich
experienced high UHI intensity in the city centre but had a relatively lower number of
vulnerable populations. Analysis of the workers’ exposure revealed that three cities consistently
showed a higher average number of workers in the service sector within Extreme UHI areas
than Non-Extreme UHI areas, likely due to the concentration of the service sector workers in
urban centres where UHI intensity is typically high. These differences highlight the need for
heat health risk assessments that consider the local context.
Our study examined the interaction between UHI exposure, demographics, and socio-economic
status in determining heat risks to health in Swiss cities. It offered a comprehensive assessment
framework for heat vulnerability explicitly tailored for key stakeholders such as urban planners
and public health officers.
Date Issued
2026-05
Publication Type
Report
Language(s)
en
Author(s)
Publisher
Access(Rights)
open.access